Pandas Profiling Report

Dataset statistics

Number of variables	17
Number of observations	2524
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	419.5 KiB
Average record size in memory	170.2 B

Variable types

Numeric	8
Categorical	6
DateTime	1
Boolean	2

Alerts

`country` has constant value "Australia"	Constant
`job_title` has a high cardinality: 195 distinct values	High cardinality
`postcode` is highly overall correlated with `property_valuation` and 1 other fields	High correlation
`property_valuation` is highly overall correlated with `postcode`	High correlation
`list_price` is highly overall correlated with `standard_cost`	High correlation
`standard_cost` is highly overall correlated with `list_price`	High correlation
`state` is highly overall correlated with `postcode`	High correlation
`deceased_indicator` is highly imbalanced (99.5%)	Imbalance
`customer_id` has unique values	Unique
`past_3_years_bike_related_purchases` has 27 (1.1%) zeros	Zeros

Reproduction

Analysis started	2023-06-12 14:02:38.900613
Analysis finished	2023-06-12 14:03:02.710659
Duration	23.81 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

customer_id
Real number (ℝ)

Distinct	2524
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1731.2254

Minimum	1
Maximum	3497
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	1
5-th percentile	173.15
Q1	848.75
median	1726.5
Q3	2600.25
95-th percentile	3314.4
Maximum	3497
Range	3496
Interquartile range (IQR)	1751.5

Descriptive statistics

Standard deviation	1009.0326
Coefficient of variation (CV)	0.58284296
Kurtosis	-1.1957022
Mean	1731.2254
Median Absolute Deviation (MAD)	876
Skewness	0.013907781
Sum	4369613
Variance	1018146.7
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	< 0.1%
2315	1	< 0.1%
2307	1	< 0.1%
2308	1	< 0.1%
2309	1	< 0.1%
2311	1	< 0.1%
2312	1	< 0.1%
2313	1	< 0.1%
2314	1	< 0.1%
2316	1	< 0.1%
Other values (2514)	2514	99.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
9	1	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
14	1	< 0.1%
15	1	< 0.1%
19	1	< 0.1%
20	1	< 0.1%
21	1	< 0.1%

Value	Count	Frequency (%)
3497	1	< 0.1%
3496	1	< 0.1%
3495	1	< 0.1%
3494	1	< 0.1%
3493	1	< 0.1%
3492	1	< 0.1%
3491	1	< 0.1%
3490	1	< 0.1%
3489	1	< 0.1%
3488	1	< 0.1%

gender
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Female	1286
Male	1238

Length

Max length	6
Median length	6
Mean length	5.0190174
Min length	4

Characters and Unicode

Total characters	12668
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Male
3rd row	Female
4th row	Male
5th row	Male

Common Values

Value	Count	Frequency (%)
Female	1286	51.0%
Male	1238	49.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
female	1286	51.0%
male	1238	49.0%

Most occurring characters

Value	Count	Frequency (%)
e	3810	30.1%
a	2524	19.9%
l	2524	19.9%
F	1286	10.2%
m	1286	10.2%
M	1238	9.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10144	80.1%
Uppercase Letter	2524	19.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	3810	37.6%
a	2524	24.9%
l	2524	24.9%
m	1286	12.7%

Uppercase Letter

Value	Count	Frequency (%)
F	1286	51.0%
M	1238	49.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12668	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	3810	30.1%
a	2524	19.9%
l	2524	19.9%
F	1286	10.2%
m	1286	10.2%
M	1238	9.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12668	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	3810	30.1%
a	2524	19.9%
l	2524	19.9%
F	1286	10.2%
m	1286	10.2%
M	1238	9.8%

past_3_years_bike_related_purchases
Real number (ℝ)

Distinct	100
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.40729

Minimum	0
Maximum	99
Zeros	27
Zeros (%)	1.1%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	25
median	48
Q3	73
95-th percentile	95
Maximum	99
Range	99
Interquartile range (IQR)	48

Descriptive statistics

Standard deviation	28.607678
Coefficient of variation (CV)	0.57901735
Kurtosis	-1.1593779
Mean	49.40729
Median Absolute Deviation (MAD)	24
Skewness	0.032630199
Sum	124704
Variance	818.39925
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2	37	1.5%
67	37	1.5%
48	35	1.4%
98	33	1.3%
35	33	1.3%
97	33	1.3%
80	33	1.3%
33	33	1.3%
53	33	1.3%
30	32	1.3%
Other values (90)	2185	86.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	27	1.1%
1	16	0.6%
2	37	1.5%
3	17	0.7%
4	24	1.0%
5	20	0.8%
6	29	1.1%
7	26	1.0%
8	15	0.6%
9	23	0.9%

Value	Count	Frequency (%)
99	26	1.0%
98	33	1.3%
97	33	1.3%
96	31	1.2%
95	19	0.8%
94	29	1.1%
93	29	1.1%
92	14	0.6%
91	21	0.8%
90	21	0.8%

DOB
Date

Distinct	2323
Distinct (%)	92.0%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Minimum	1931-10-23 00:00:00
Maximum	2002-03-11 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

age
Real number (ℝ)

Distinct	52
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	45.078447

Minimum	21
Maximum	91
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	21
5-th percentile	24
Q1	36
median	45
Q3	54
95-th percentile	66
Maximum	91
Range	70
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	12.498251
Coefficient of variation (CV)	0.27725559
Kurtosis	-0.72416444
Mean	45.078447
Median Absolute Deviation (MAD)	9
Skewness	0.032449955
Sum	113778
Variance	156.20629
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
45	157	6.2%
46	117	4.6%
44	109	4.3%
49	98	3.9%
48	96	3.8%
42	76	3.0%
47	74	2.9%
37	73	2.9%
43	73	2.9%
35	56	2.2%
Other values (42)	1595	63.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
21	16	0.6%
22	24	1.0%
23	36	1.4%
24	54	2.1%
25	51	2.0%
26	40	1.6%
27	47	1.9%
28	52	2.1%
29	43	1.7%
30	50	2.0%

Value	Count	Frequency (%)
91	1	< 0.1%
87	1	< 0.1%
79	2	0.1%
69	32	1.3%
68	33	1.3%
67	38	1.5%
66	36	1.4%
65	35	1.4%
64	48	1.9%
63	46	1.8%

job_title
Categorical

Distinct	195
Distinct (%)	7.7%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Social Worker	36
Chemical Engineer	34
Registered Nurse	32
Nuclear Power Engineer	32
Assistant Media Planner	32
Other values (190)	2358

Length

Max length	36
Median length	25
Mean length	18.076862
Min length	5

Characters and Unicode

Total characters	45626
Distinct characters	47
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.1%

Sample

1st row	Executive Secretary
2nd row	Administrative Officer
3rd row	Business Systems Development Analyst
4th row	Nuclear Power Engineer
5th row	Developer I

Common Values

Value	Count	Frequency (%)
Social Worker	36	1.4%
Chemical Engineer	34	1.3%
Registered Nurse	32	1.3%
Nuclear Power Engineer	32	1.3%
Assistant Media Planner	32	1.3%
Internal Auditor	31	1.2%
Dental Hygienist	31	1.2%
Legal Assistant	30	1.2%
Research Nurse	30	1.2%
Desktop Support Technician	29	1.1%
Other values (185)	2207	87.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
engineer	364	6.2%
assistant	238	4.1%
analyst	190	3.2%
manager	189	3.2%
iv	150	2.6%
i	148	2.5%
iii	142	2.4%
ii	133	2.3%
senior	126	2.1%
systems	121	2.1%
Other values (117)	4073	69.3%

Most occurring characters

Value	Count	Frequency (%)
e	4469	9.8%
n	3500	7.7%
t	3481	7.6%
a	3425	7.5%
i	3358	7.4%
	3350	7.3%
r	2963	6.5%
s	2769	6.1%
o	2098	4.6%
c	2018	4.4%
Other values (37)	14195	31.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	35692	78.2%
Uppercase Letter	6562	14.4%
Space Separator	3350	7.3%
Other Punctuation	22	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	4469	12.5%
n	3500	9.8%
t	3481	9.8%
a	3425	9.6%
i	3358	9.4%
r	2963	8.3%
s	2769	7.8%
o	2098	5.9%
c	2018	5.7%
l	1467	4.1%
Other values (14)	6144	17.2%

Uppercase Letter

Value	Count	Frequency (%)
I	1060	16.2%
A	1017	15.5%
S	789	12.0%
E	528	8.0%
P	492	7.5%
C	393	6.0%
D	336	5.1%
M	310	4.7%
V	263	4.0%
T	238	3.6%
Other values (11)	1136	17.3%

Space Separator

Value	Count	Frequency (%)
	3350	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	22	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	42254	92.6%
Common	3372	7.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	4469	10.6%
n	3500	8.3%
t	3481	8.2%
a	3425	8.1%
i	3358	7.9%
r	2963	7.0%
s	2769	6.6%
o	2098	5.0%
c	2018	4.8%
l	1467	3.5%
Other values (35)	12706	30.1%

Common

Value	Count	Frequency (%)
	3350	99.3%
/	22	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45626	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	4469	9.8%
n	3500	7.7%
t	3481	7.6%
a	3425	7.5%
i	3358	7.4%
	3350	7.3%
r	2963	6.5%
s	2769	6.1%
o	2098	4.6%
c	2018	4.4%
Other values (37)	14195	31.1%

job_industry_category
Categorical

Distinct	9
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Manufacturing	615
Financial Services	607
Health	480
Retail	260
Property	202
Other values (4)	360

Length

Max length	18
Median length	13
Mean length	11.317353
Min length	2

Characters and Unicode

Total characters	28565
Distinct characters	29
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Health
2nd row	Financial Services
3rd row	Argiculture
4th row	Manufacturing
5th row	Financial Services

Common Values

Value	Count	Frequency (%)
Manufacturing	615	24.4%
Financial Services	607	24.0%
Health	480	19.0%
Retail	260	10.3%
Property	202	8.0%
Entertainment	111	4.4%
IT	108	4.3%
Argiculture	87	3.4%
Telecommunications	54	2.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
manufacturing	615	19.6%
financial	607	19.4%
services	607	19.4%
health	480	15.3%
retail	260	8.3%
property	202	6.5%
entertainment	111	3.5%
it	108	3.4%
argiculture	87	2.8%
telecommunications	54	1.7%

Most occurring characters

Value	Count	Frequency (%)
a	3349	11.7%
i	3002	10.5%
n	2885	10.1%
e	2573	9.0%
t	2031	7.1%
c	2024	7.1%
r	1911	6.7%
l	1488	5.2%
u	1458	5.1%
g	702	2.5%
Other values (19)	7142	25.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	24719	86.5%
Uppercase Letter	3239	11.3%
Space Separator	607	2.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	3349	13.5%
i	3002	12.1%
n	2885	11.7%
e	2573	10.4%
t	2031	8.2%
c	2024	8.2%
r	1911	7.7%
l	1488	6.0%
u	1458	5.9%
g	702	2.8%
Other values (8)	3296	13.3%

Uppercase Letter

Value	Count	Frequency (%)
M	615	19.0%
F	607	18.7%
S	607	18.7%
H	480	14.8%
R	260	8.0%
P	202	6.2%
T	162	5.0%
E	111	3.4%
I	108	3.3%
A	87	2.7%

Space Separator

Value	Count	Frequency (%)
	607	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	27958	97.9%
Common	607	2.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	3349	12.0%
i	3002	10.7%
n	2885	10.3%
e	2573	9.2%
t	2031	7.3%
c	2024	7.2%
r	1911	6.8%
l	1488	5.3%
u	1458	5.2%
g	702	2.5%
Other values (18)	6535	23.4%

Common

Value	Count	Frequency (%)
	607	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	28565	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	3349	11.7%
i	3002	10.5%
n	2885	10.1%
e	2573	9.0%
t	2031	7.1%
c	2024	7.1%
r	1911	6.7%
l	1488	5.2%
u	1458	5.1%
g	702	2.5%
Other values (19)	7142	25.0%

wealth_segment
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Mass Customer	1249
High Net Worth	650
Affluent Customer	625

Length

Max length	17
Median length	14
Mean length	14.248019
Min length	13

Characters and Unicode

Total characters	35962
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mass Customer
2nd row	Mass Customer
3rd row	Affluent Customer
4th row	Mass Customer
5th row	High Net Worth

Common Values

Value	Count	Frequency (%)
Mass Customer	1249	49.5%
High Net Worth	650	25.8%
Affluent Customer	625	24.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
customer	1874	32.9%
mass	1249	21.9%
high	650	11.4%
net	650	11.4%
worth	650	11.4%
affluent	625	11.0%

Most occurring characters

Value	Count	Frequency (%)
s	4372	12.2%
t	3799	10.6%
	3174	8.8%
e	3149	8.8%
r	2524	7.0%
o	2524	7.0%
u	2499	6.9%
C	1874	5.2%
m	1874	5.2%
h	1300	3.6%
Other values (11)	8873	24.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	27090	75.3%
Uppercase Letter	5698	15.8%
Space Separator	3174	8.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	4372	16.1%
t	3799	14.0%
e	3149	11.6%
r	2524	9.3%
o	2524	9.3%
u	2499	9.2%
m	1874	6.9%
h	1300	4.8%
f	1250	4.6%
a	1249	4.6%
Other values (4)	2550	9.4%

Uppercase Letter

Value	Count	Frequency (%)
C	1874	32.9%
M	1249	21.9%
H	650	11.4%
N	650	11.4%
W	650	11.4%
A	625	11.0%

Space Separator

Value	Count	Frequency (%)
	3174	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	32788	91.2%
Common	3174	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	4372	13.3%
t	3799	11.6%
e	3149	9.6%
r	2524	7.7%
o	2524	7.7%
u	2499	7.6%
C	1874	5.7%
m	1874	5.7%
h	1300	4.0%
f	1250	3.8%
Other values (10)	7623	23.2%

Common

Value	Count	Frequency (%)
	3174	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	35962	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	4372	12.2%
t	3799	10.6%
	3174	8.8%
e	3149	8.8%
r	2524	7.0%
o	2524	7.0%
u	2499	6.9%
C	1874	5.2%
m	1874	5.2%
h	1300	3.6%
Other values (11)	8873	24.7%

deceased_indicator
Boolean

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	22.2 KiB

False	2523
True	1

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	2523	> 99.9%
True	1	< 0.1%

owns_car
Boolean

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	22.2 KiB

True	1288
False	1236

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	1288	51.0%
False	1236	49.0%

tenure
Real number (ℝ)

Distinct	22
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.719097

Minimum	1
Maximum	22
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	6
median	11
Q3	16
95-th percentile	20
Maximum	22
Range	21
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.6811096
Coefficient of variation (CV)	0.52999891
Kurtosis	-1.04804
Mean	10.719097
Median Absolute Deviation (MAD)	5
Skewness	0.049897068
Sum	27055
Variance	32.275006
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
7	146	5.8%
16	145	5.7%
11	142	5.6%
12	142	5.6%
8	141	5.6%
5	139	5.5%
14	136	5.4%
18	132	5.2%
9	132	5.2%
10	131	5.2%
Other values (12)	1138	45.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	111	4.4%
2	95	3.8%
3	106	4.2%
4	118	4.7%
5	139	5.5%
6	119	4.7%
7	146	5.8%
8	141	5.6%
9	132	5.2%
10	131	5.2%

Value	Count	Frequency (%)
22	38	1.5%
21	38	1.5%
20	64	2.5%
19	106	4.2%
18	132	5.2%
17	113	4.5%
16	145	5.7%
15	101	4.0%
14	136	5.4%
13	129	5.1%

postcode
Real number (ℝ)

Distinct	762
Distinct (%)	30.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2993.8879

Minimum	2000
Maximum	4883
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	2000
5-th percentile	2049
Q1	2196.75
median	2767
Q3	3787.25
95-th percentile	4551
Maximum	4883
Range	2883
Interquartile range (IQR)	1590.5

Descriptive statistics

Standard deviation	857.19613
Coefficient of variation (CV)	0.28631538
Kurtosis	-0.95621377
Mean	2993.8879
Median Absolute Deviation (MAD)	601
Skewness	0.61140107
Sum	7556573
Variance	734785.21
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2155	20	0.8%
2170	20	0.8%
2153	19	0.8%
2145	19	0.8%
2166	16	0.6%
3977	16	0.6%
2567	16	0.6%
2148	15	0.6%
2759	14	0.6%
2261	14	0.6%
Other values (752)	2355	93.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2000	6	0.2%
2007	2	0.1%
2008	1	< 0.1%
2009	3	0.1%
2010	8	0.3%
2011	1	< 0.1%
2015	5	0.2%
2016	5	0.2%
2017	5	0.2%
2018	3	0.1%

Value	Count	Frequency (%)
4883	1	< 0.1%
4878	3	0.1%
4877	1	< 0.1%
4873	1	< 0.1%
4870	7	0.3%
4869	5	0.2%
4868	3	0.1%
4860	1	< 0.1%
4825	5	0.2%
4820	4	0.2%

state
Categorical

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

NSW	1346
VIC	575
QLD	546
Victoria	57

Length

Max length	8
Median length	3
Mean length	3.112916
Min length	3

Characters and Unicode

Total characters	7857
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NSW
2nd row	NSW
3rd row	NSW
4th row	QLD
5th row	VIC

Common Values

Value	Count	Frequency (%)
NSW	1346	53.3%
VIC	575	22.8%
QLD	546	21.6%
Victoria	57	2.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
nsw	1346	53.3%
vic	575	22.8%
qld	546	21.6%
victoria	57	2.3%

Most occurring characters

Value	Count	Frequency (%)
N	1346	17.1%
S	1346	17.1%
W	1346	17.1%
V	632	8.0%
I	575	7.3%
C	575	7.3%
Q	546	6.9%
L	546	6.9%
D	546	6.9%
i	114	1.5%
Other values (5)	285	3.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	7458	94.9%
Lowercase Letter	399	5.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	1346	18.0%
S	1346	18.0%
W	1346	18.0%
V	632	8.5%
I	575	7.7%
C	575	7.7%
Q	546	7.3%
L	546	7.3%
D	546	7.3%

Lowercase Letter

Value	Count	Frequency (%)
i	114	28.6%
c	57	14.3%
t	57	14.3%
o	57	14.3%
r	57	14.3%
a	57	14.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7857	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	1346	17.1%
S	1346	17.1%
W	1346	17.1%
V	632	8.0%
I	575	7.3%
C	575	7.3%
Q	546	6.9%
L	546	6.9%
D	546	6.9%
i	114	1.5%
Other values (5)	285	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7857	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	1346	17.1%
S	1346	17.1%
W	1346	17.1%
V	632	8.0%
I	575	7.3%
C	575	7.3%
Q	546	6.9%
L	546	6.9%
D	546	6.9%
i	114	1.5%
Other values (5)	285	3.6%

country
Categorical

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	39.4 KiB

Australia	2524

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	22716
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Australia
2nd row	Australia
3rd row	Australia
4th row	Australia
5th row	Australia

Common Values

Value	Count	Frequency (%)
Australia	2524	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
australia	2524	100.0%

Most occurring characters

Value	Count	Frequency (%)
a	5048	22.2%
A	2524	11.1%
u	2524	11.1%
s	2524	11.1%
t	2524	11.1%
r	2524	11.1%
l	2524	11.1%
i	2524	11.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	20192	88.9%
Uppercase Letter	2524	11.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	5048	25.0%
u	2524	12.5%
s	2524	12.5%
t	2524	12.5%
r	2524	12.5%
l	2524	12.5%
i	2524	12.5%

Uppercase Letter

Value	Count	Frequency (%)
A	2524	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	22716	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	5048	22.2%
A	2524	11.1%
u	2524	11.1%
s	2524	11.1%
t	2524	11.1%
r	2524	11.1%
l	2524	11.1%
i	2524	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	22716	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	5048	22.2%
A	2524	11.1%
u	2524	11.1%
s	2524	11.1%
t	2524	11.1%
r	2524	11.1%
l	2524	11.1%
i	2524	11.1%

property_valuation
Real number (ℝ)

Distinct	12
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.479794

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	6
median	8
Q3	10
95-th percentile	11
Maximum	12
Range	11
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.8329057
Coefficient of variation (CV)	0.37874114
Kurtosis	-0.36388935
Mean	7.479794
Median Absolute Deviation (MAD)	2
Skewness	-0.62675131
Sum	18879
Variance	8.0253545
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
9	422	16.7%
8	410	16.2%
10	354	14.0%
7	296	11.7%
11	174	6.9%
6	151	6.0%
5	149	5.9%
4	146	5.8%
12	119	4.7%
3	108	4.3%
Other values (2)	195	7.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	102	4.0%
2	93	3.7%
3	108	4.3%
4	146	5.8%
5	149	5.9%
6	151	6.0%
7	296	11.7%
8	410	16.2%
9	422	16.7%
10	354	14.0%

Value	Count	Frequency (%)
12	119	4.7%
11	174	6.9%
10	354	14.0%
9	422	16.7%
8	410	16.2%
7	296	11.7%
6	151	6.0%
5	149	5.9%
4	146	5.8%
3	108	4.3%

list_price
Real number (ℝ)

Distinct	2518
Distinct (%)	99.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1108.6353

Minimum	60.34
Maximum	2091.47
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	60.34
5-th percentile	659.79133
Q1	930.76075
median	1112.735
Q3	1285.3882
95-th percentile	1564.9388
Maximum	2091.47
Range	2031.13
Interquartile range (IQR)	354.6275

Descriptive statistics

Standard deviation	282.60337
Coefficient of variation (CV)	0.25491103
Kurtosis	0.54084619
Mean	1108.6353
Median Absolute Deviation (MAD)	177.451
Skewness	-0.085698705
Sum	2798195.6
Variance	79864.667
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2005.66	2	0.1%
774.53	2	0.1%
441.49	2	0.1%
681.23	2	0.1%
1018.74	2	0.1%
937.575	2	0.1%
1275.174	1	< 0.1%
1348.43	1	< 0.1%
1202.338	1	< 0.1%
1234.66	1	< 0.1%
Other values (2508)	2508	99.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
60.34	1	< 0.1%
71.49	1	< 0.1%
100.35	1	< 0.1%
127.675	1	< 0.1%
139.6033333	1	< 0.1%
153.395	1	< 0.1%
180.89	1	< 0.1%
193.24	1	< 0.1%
202.5933333	1	< 0.1%
202.62	1	< 0.1%

Value	Count	Frequency (%)
2091.47	1	< 0.1%
2083.94	1	< 0.1%
2023.004	1	< 0.1%
2005.66	2	0.1%
1977.36	1	< 0.1%
1952.11	1	< 0.1%
1936.856667	1	< 0.1%
1934.635	1	< 0.1%
1930.87	1	< 0.1%
1893.73	1	< 0.1%

standard_cost
Real number (ℝ)

Distinct	2513
Distinct (%)	99.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	559.29735

Minimum	44.985
Maximum	1759.85
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	39.4 KiB

Quantile statistics

Minimum	44.985
5-th percentile	272.53917
Q1	426.42325
median	550.25746
Q3	675.42994
95-th percentile	878.60517
Maximum	1759.85
Range	1714.865
Interquartile range (IQR)	249.00669

Descriptive statistics

Standard deviation	192.94416
Coefficient of variation (CV)	0.34497599
Kurtosis	1.5680607
Mean	559.29735
Median Absolute Deviation (MAD)	124.47078
Skewness	0.61090109
Sum	1411666.5
Variance	37227.448
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
827.8933333	2	0.1%
561.555	2	0.1%
528.43	2	0.1%
602.4766667	2	0.1%
593.82	2	0.1%
246.6266667	2	0.1%
1203.4	2	0.1%
448.9	2	0.1%
792.64625	2	0.1%
464.72	2	0.1%
Other values (2503)	2504	99.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
44.985	1	< 0.1%
45.26	1	< 0.1%
53.62	1	< 0.1%
55.68	1	< 0.1%
74.51	1	< 0.1%
75.26	1	< 0.1%
84.99	2	0.1%
91	1	< 0.1%
95.76	1	< 0.1%
101.1325	1	< 0.1%

Value	Count	Frequency (%)
1759.85	1	< 0.1%
1610.9	1	< 0.1%
1459.415	1	< 0.1%
1356.5475	1	< 0.1%
1335.423333	1	< 0.1%
1323.145	1	< 0.1%
1288.93	1	< 0.1%
1287.978	1	< 0.1%
1259.36	1	< 0.1%
1234.156667	1	< 0.1%

Auto

Heatmap
Table

	customer_id	past_3_years_bike_related_purchases	age	tenure	postcode	property_valuation	list_price	standard_cost	gender	job_industry_category	wealth_segment	deceased_indicator	owns_car	state
customer_id	1.000	-0.002	-0.001	-0.015	0.030	-0.014	0.029	0.024	0.004	0.025	0.024	0.016	0.048	0.244
past_3_years_bike_related_purchases	-0.002	1.000	-0.047	-0.015	-0.010	0.009	0.012	-0.016	0.038	0.000	0.000	0.017	0.000	0.000
age	-0.001	-0.047	1.000	0.424	-0.023	0.015	-0.000	0.001	0.000	0.000	0.000	0.000	0.000	0.051
tenure	-0.015	-0.015	0.424	1.000	-0.003	-0.024	0.001	-0.036	0.035	0.018	0.000	0.000	0.014	0.000
postcode	0.030	-0.010	-0.023	-0.003	1.000	-0.578	0.026	0.011	0.033	0.000	0.000	0.029	0.000	0.793
property_valuation	-0.014	0.009	0.015	-0.024	-0.578	1.000	-0.013	0.009	0.000	0.000	0.014	0.073	0.021	0.254
list_price	0.029	0.012	-0.000	0.001	0.026	-0.013	1.000	0.530	0.030	0.000	0.000	0.045	0.079	0.000
standard_cost	0.024	-0.016	0.001	-0.036	0.011	0.009	0.530	1.000	0.000	0.008	0.000	0.000	0.012	0.000
gender	0.004	0.038	0.000	0.035	0.033	0.000	0.030	0.000	1.000	0.000	0.019	0.000	0.000	0.000
job_industry_category	0.025	0.000	0.000	0.018	0.000	0.000	0.000	0.008	0.000	1.000	0.021	0.000	0.019	0.021
wealth_segment	0.024	0.000	0.000	0.000	0.000	0.014	0.000	0.000	0.019	0.021	1.000	0.020	0.021	0.000
deceased_indicator	0.016	0.017	0.000	0.000	0.029	0.073	0.045	0.000	0.000	0.000	0.020	1.000	0.000	0.000
owns_car	0.048	0.000	0.000	0.014	0.000	0.021	0.079	0.012	0.000	0.019	0.021	0.000	1.000	0.000
state	0.244	0.000	0.051	0.000	0.793	0.254	0.000	0.000	0.000	0.021	0.000	0.000	0.000	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	customer_id	gender	past_3_years_bike_related_purchases	DOB	age	job_title	job_industry_category	wealth_segment	deceased_indicator	owns_car	tenure	postcode	state	country	property_valuation	list_price	standard_cost
0	1	Female	93	1953-10-12	69	Executive Secretary	Health	Mass Customer	N	Yes	11.0	2016	NSW	Australia	10	825.859091	551.487273
1	2	Male	81	1980-12-16	42	Administrative Officer	Financial Services	Mass Customer	N	Yes	16.0	2153	NSW	Australia	10	1383.023333	640.936667
2	9	Female	97	1973-03-10	50	Business Systems Development Analyst	Argiculture	Affluent Customer	N	Yes	8.0	2023	NSW	Australia	12	892.925000	500.740000
3	12	Male	58	1994-07-21	28	Nuclear Power Engineer	Manufacturing	Mass Customer	N	No	8.0	4557	QLD	Australia	4	913.458571	407.740000
4	13	Male	38	1955-02-15	68	Developer I	Financial Services	High Net Worth	N	Yes	8.0	3799	VIC	Australia	6	1104.962857	485.337143
5	14	Female	85	1983-03-25	40	Account Executive	Financial Services	Affluent Customer	N	No	6.0	2760	NSW	Australia	8	898.392500	265.163333
6	15	Male	91	2000-07-13	22	Junior Executive	Manufacturing	Mass Customer	N	No	1.0	2428	NSW	Australia	9	820.556667	532.491667
7	19	Female	76	2001-04-15	22	Geological Engineer	Manufacturing	High Net Worth	N	No	1.0	2233	NSW	Australia	9	1412.730000	428.800000
8	20	Male	72	1980-08-13	42	Project Manager	Manufacturing	Mass Customer	N	No	11.0	2444	NSW	Australia	8	1654.715000	752.645000
9	21	Male	74	1980-09-20	42	Safety Technician I	Manufacturing	Affluent Customer	N	Yes	16.0	2650	NSW	Australia	7	1489.242000	643.360000

	customer_id	gender	past_3_years_bike_related_purchases	DOB	age	job_title	job_industry_category	wealth_segment	deceased_indicator	owns_car	tenure	postcode	state	country	property_valuation	list_price	standard_cost
2514	3488	Male	63	1975-08-07	47	Speech Pathologist	Manufacturing	Mass Customer	N	Yes	9.0	2136	NSW	Australia	10	1083.895000	675.920000
2515	3489	Female	90	1969-10-30	53	Help Desk Operator	Argiculture	Mass Customer	N	Yes	9.0	2099	NSW	Australia	11	1383.358333	942.618333
2516	3490	Male	45	1980-06-21	42	VP Product Management	Financial Services	High Net Worth	N	No	14.0	2126	NSW	Australia	10	947.940000	472.026000
2517	3491	Female	69	1976-04-03	47	Business Systems Development Analyst	Financial Services	Affluent Customer	N	No	10.0	3195	VIC	Australia	10	787.917500	430.347500
2518	3492	Male	83	1966-01-27	57	Civil Engineer	Manufacturing	Mass Customer	N	No	19.0	3021	VIC	Australia	9	1380.476667	649.206667
2519	3493	Male	30	1964-02-29	59	Research Assistant I	Health	High Net Worth	N	No	18.0	2090	NSW	Australia	10	1675.636667	1054.156667
2520	3494	Male	72	1998-12-24	24	Account Representative IV	Argiculture	High Net Worth	N	No	1.0	2033	NSW	Australia	10	1280.677500	591.900000
2521	3495	Female	57	1987-07-12	35	Programmer III	Financial Services	High Net Worth	N	No	8.0	2767	NSW	Australia	9	1232.378571	682.714286
2522	3496	Male	99	1986-04-25	37	Editor	Manufacturing	Mass Customer	N	Yes	19.0	2171	NSW	Australia	9	1181.345000	669.885000
2523	3497	Female	73	1986-05-03	37	Administrative Assistant IV	Manufacturing	Affluent Customer	N	Yes	18.0	3976	VIC	Australia	5	1248.023333	698.583333

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length